Find best overlap threshold for EnrichMap
mem_find_overlap(
mem,
overlap_range = c(0.1, 0.99),
overlap_count = 2,
node_fraction = 0.5,
max_cutoff = 0.4,
debug = FALSE,
...
)
list
output from multiEnrichMap()
numeric range of Jaccard overlap values
numeric value passed to mem_multienrichplot()
which is used to filter the multienrichmap by Jaccard overlap
and by overlap_count.
numeric value between 0 and 1, to define the maximum fraction of nodes in the largest connected component, compared to the total number of non-singlet nodes.
logical indicating whether to return full debug data, which is used internally to determine the best overlap cutoff to use.
This function implements a straightforward approach to determine
a reasonable Jaccard overlap threshold for EnrichMap data.
It finds the overlap threshold at which the first connected
component is no more than max_cutoff
fraction of the whole
network. This fraction is defined as the number of nodes in the
largest connected component, divided by the total number of
non-singlet nodes. When all nodes are connected, this fraction == 1.
We found empirically that a max_cutoff=0.4
, the point at which the
largest connected component contains no more than 40% of all nodes,
seems to be a reasonably good place to start.
Other jam utility functions:
avg_angles()
,
avg_colors_by_list()
,
call_fn_ellipsis_deprecated()
,
cell_fun_bivariate()
,
collapse_mem_clusters()
,
colorRamp2D()
,
deconcat_df2()
,
display_colorRamp2D()
,
enrichList2geneHitList()
,
filter_mem_genes()
,
filter_mem_sets()
,
find_colname()
,
get_hull_data()
,
get_igraph_layout()
,
gsubs_remove()
,
handle_igraph_param_list()
,
isColorBlank()
,
make_legend_bivariate()
,
make_point_hull()
,
order_colors()
,
rank_mem_clusters()
,
rotate_coordinates()
,
subgraph_jam()
,
subset_mem()
,
summarize_node_spacing()
,
xyAngle()